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Chi-Square Tests😊🛑

- Purpose: Tests whether there is a significant association between two categorical variables.

- Key Statistics:

- Pearson Chi-Square: The most common chi-square test for independence. Assumes expected frequencies are ≥5 in most cells.

- Likelihood Ratio: An alternative to Pearson’s chi-square, useful for small samples or sparse tables.

- Linear-by-Linear Association: Tests for a linear trend between ordinal variables.

- Note: If >20% of cells have expected counts <5, consider Fisher’s Exact Test (better for small samples).

This is a quick look..I will move forward with more untouched, technical details in my future posts😊😊



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Chi-Square Tests😊🛑

- Purpose: Tests whether there is a significant association between two categorical variables.

- Key Statistics:

- Pearson Chi-Square: The most common chi-square test for independence. Assumes expected frequencies are ≥5 in most cells.

- Likelihood Ratio: An alternative to Pearson’s chi-square, useful for small samples or sparse tables.

- Linear-by-Linear Association: Tests for a linear trend between ordinal variables.

- Note: If >20% of cells have expected counts <5, consider Fisher’s Exact Test (better for small samples).

This is a quick look..I will move forward with more untouched, technical details in my future posts😊😊

BY Research Methods in AL


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